Affiliation:
1. Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Mechanical Engineering, , Tianjin 300401 , China
2. Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, , Changsha 410082 , China
Abstract
Abstract
In the design of artillery external ballistics, sensitivity analysis can effectively quantify the influence of multi-source uncertain parameters on the dispersion of projectile landing points to improve the precise attack ability of artillery. However, for a complicated artillery external ballistic system containing multiple inputs and outputs, its mapping relationships are not definite under uncertainty and it is difficult to estimate a comprehensive sensitivity index due to involving the calculation of high dimensional integral. Therefore, a sensitivity analysis method based on the combination of variance and covariance decomposition with the approximate high dimensional model representation (AHDMR) is proposed to measure the influence of muzzle state parameters, projectile characteristic parameters, etc. on projectile landing points under uncertainty in this paper. First, we establish the numerical simulation model of artillery external ballistics by combing the external ballistic theory and Runge–Kutta algorithm to acquire the mapping relationships between the uncertain input parameters and the dispersion of projectile landing points and implement uncertainty analysis under different uncertainty levels (UL) and distributions. Then, with the use of a set of orthogonal polynomials for uniform and Gaussian distribution, respectively, the high dimensional model representation of the mapping relationship is approximately expressed and the compressive sensitivity indices can be effectively estimated based on the Monte Carlo simulation. Moreover, the comparison results of two numerical examples indicate the proposed sensitivity analysis method is accurate and practical. Finally, through the method, the importance rankings of multi-uncertain parameters on projectile landing points for two distributions are effectively quantified under the UL = [0.01, 0.02, 0.03, 0.04, 0.05].
Funder
National Natural Science Foundation of China
Science Fund for Creative Research Groups
Subject
Computer Graphics and Computer-Aided Design,Computer Science Applications,Mechanical Engineering,Mechanics of Materials
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